SOTAVerified

Machine Translation

Machine translation is the task of translating a sentence in a source language to a different target language.

Approaches for machine translation can range from rule-based to statistical to neural-based. More recently, encoder-decoder attention-based architectures like BERT have attained major improvements in machine translation.

One of the most popular datasets used to benchmark machine translation systems is the WMT family of datasets. Some of the most commonly used evaluation metrics for machine translation systems include BLEU, METEOR, NIST, and others.

( Image credit: Google seq2seq )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1251–1300 of 10752 papers

TitleStatusHype
Scaling Laws of Decoder-Only Models on the Multilingual Machine Translation Task—0
Choose the Final Translation from NMT and LLM hypotheses Using MBR Decoding: HW-TSC's Submission to the WMT24 General MT Shared Task—0
FAMOUS: Flexible Accelerator for the Attention Mechanism of Transformer on UltraScale+ FPGAs—0
ProTEA: Programmable Transformer Encoder Acceleration on FPGA—0
EMMeTT: Efficient Multimodal Machine Translation Training—0
Enhancing E-commerce Product Title Translation with Retrieval-Augmented Generation and Large Language Models—0
AraDiCE: Benchmarks for Dialectal and Cultural Capabilities in LLMs—0
GOSt-MT: A Knowledge Graph for Occupation-related Gender Biases in Machine Translation—0
Task Arithmetic for Language Expansion in Speech Translation—0
American Sign Language to Text Translation using Transformer and Seq2Seq with LSTM—0
Thesis proposal: Are We Losing Textual Diversity to Natural Language Processing?—0
Machine Translation with Large Language Models: Decoder Only vs. Encoder-Decoder—0
BLens: Contrastive Captioning of Binary Functions using Ensemble Embedding—0
Cross-Attention Based Influence Model for Manual and Nonmanual Sign Language Analysis—0
Reranking Laws for Language Generation: A Communication-Theoretic Perspective—0
Translating Step-by-Step: Decomposing the Translation Process for Improved Translation Quality of Long-Form Texts—0
Vision-fused Attack: Advancing Aggressive and Stealthy Adversarial Text against Neural Machine TranslationCode0
Evaluation of Google Translate for Mandarin Chinese translation using sentiment and semantic analysisCode0
Exploring Intrinsic Language-specific Subspaces in Fine-tuning Multilingual Neural Machine TranslationCode0
Open Language Data Initiative: Advancing Low-Resource Machine Translation for Karakalpak—0
From Calculation to Adjudication: Examining LLM judges on Mathematical Reasoning Tasks—0
N-gram Prediction and Word Difference Representations for Language Modeling—0
Creating Domain-Specific Translation Memories for Machine Translation Fine-tuning: The TRENCARD Bilingual Cardiology Corpus—0
A Data Selection Approach for Enhancing Low Resource Machine Translation Using Cross-Lingual Sentence Representations—0
Towards Cross-Lingual Explanation of Artwork in Large-scale Vision Language Models—0
Correcting FLORES Evaluation Dataset for Four African Languages—0
Towards Tailored Recovery of Lexical Diversity in Literary Machine Translation—0
InkubaLM: A small language model for low-resource African languages—0
MQM-Chat: Multidimensional Quality Metrics for Chat Translation—0
Instruction-tuned Large Language Models for Machine Translation in the Medical Domain—0
An Investigation of Warning Erroneous Chat Translations in Cross-lingual Communication—0
A global AI community requires language-diverse publishing—0
Pitfalls and Outlooks in Using COMETCode0
From Rule-Based Models to Deep Learning Transformers Architectures for Natural Language Processing and Sign Language Translation Systems: Survey, Taxonomy and Performance Evaluation—0
What Makes a Good Story and How Can We Measure It? A Comprehensive Survey of Story Evaluation—0
LowCLIP: Adapting the CLIP Model Architecture for Low-Resource Languages in Multimodal Image Retrieval TaskCode0
Bidirectional Awareness Induction in Autoregressive Seq2Seq Models—0
FLEURS-ASL: Including American Sign Language in Massively Multilingual Multitask Evaluation—0
Integrating Multi-Head Convolutional Encoders with Cross-Attention for Improved SPARQL Query Translation—0
Cultural Adaptation of Menus: A Fine-Grained Approach—0
Quality or Quantity? On Data Scale and Diversity in Adapting Large Language Models for Low-Resource Translation—0
High-Quality Data Augmentation for Low-Resource NMT: Combining a Translation Memory, a GAN Generator, and Filtering—0
Distributional Properties of Subword Regularization—0
Expanding FLORES+ Benchmark for more Low-Resource Settings: Portuguese-Emakhuwa Machine Translation Evaluation—0
Defining Boundaries: The Impact of Domain Specification on Cross-Language and Cross-Domain Transfer in Machine Translation—0
IKUN for WMT24 General MT Task: LLMs Are here for Multilingual Machine Translation—0
Towards Inducing Document-Level Abilities in Standard Multilingual Neural Machine Translation Models—0
Plug, Play, and Fuse: Zero-Shot Joint Decoding via Word-Level Re-ranking Across Diverse Vocabularies—0
Large Language Models for Classical Chinese Poetry Translation: Benchmarking, Evaluating, and Improving—0
Improving Rare Word Translation With Dictionaries and Attention MaskingCode0
Show:102550
← PrevPage 26 of 216Next →
All datasetsWMT2014 English-GermanWMT2014 English-FrenchIWSLT2014 German-EnglishACESWMT2016 English-RomanianWMT2016 Romanian-EnglishWMT2014 German-EnglishIWSLT2015 German-EnglishWMT2016 English-GermanIWSLT2015 English-VietnameseIWSLT2015 English-GermanWMT2016 German-English

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Transformer Cycle (Rev)BLEU score35.14—Unverified
2Noisy back-translationBLEU score35—Unverified
3Transformer+Rep(Uni)BLEU score33.89—Unverified
4T5-11BBLEU score32.1—Unverified
5BiBERTBLEU score31.26—Unverified
6Transformer + R-DropBLEU score30.91—Unverified
7Bi-SimCutBLEU score30.78—Unverified
8BERT-fused NMTBLEU score30.75—Unverified
9Data Diversification - TransformerBLEU score30.7—Unverified
10SimCutBLEU score30.56—Unverified
#ModelMetricClaimedVerifiedStatus
1Transformer+BT (ADMIN init)BLEU score46.4—Unverified
2Noisy back-translationBLEU score45.6—Unverified
3mRASP+Fine-TuneBLEU score44.3—Unverified
4Transformer + R-DropBLEU score43.95—Unverified
5Transformer (ADMIN init)BLEU score43.8—Unverified
6AdminBLEU score43.8—Unverified
7BERT-fused NMTBLEU score43.78—Unverified
8MUSE(Paralllel Multi-scale Attention)BLEU score43.5—Unverified
9T5BLEU score43.4—Unverified
10Local Joint Self-attentionBLEU score43.3—Unverified
#ModelMetricClaimedVerifiedStatus
1PiNMTBLEU score40.43—Unverified
2BiBERTBLEU score38.61—Unverified
3Bi-SimCutBLEU score38.37—Unverified
4Cutoff + Relaxed Attention + LMBLEU score37.96—Unverified
5DRDABLEU score37.95—Unverified
6Transformer + R-Drop + CutoffBLEU score37.9—Unverified
7SimCutBLEU score37.81—Unverified
8Cutoff+KneeBLEU score37.78—Unverified
9CutoffBLEU score37.6—Unverified
10CipherDAugBLEU score37.53—Unverified
#ModelMetricClaimedVerifiedStatus
1HWTSC-Teacher-SimScore19.97—Unverified
2MS-COMET-22Score19.89—Unverified
3MS-COMET-QE-22Score19.76—Unverified
4KG-BERTScoreScore17.28—Unverified
5metricx_xl_DA_2019Score17.17—Unverified
6COMET-QEScore16.8—Unverified
7COMET-22Score16.31—Unverified
8UniTE-srcScore15.68—Unverified
9UniTE-refScore15.38—Unverified
10metricx_xxl_DA_2019Score15.24—Unverified